Healthcare-associated infections (HAIs), particularly those due to antimicrobial-resistant pathogens, are very common and are associated with significant increases in morbidity, mortality, and cost. Antimicrobial resistance has increased markedly in recent years due to overuse of antimicrobials. However, efforts to limit unnecessary antibiotic use have met with little success. Inappropriate antibiotic use is largely driven by the inability to identify conditions for which empiric antibiotics are unnecessary. The role of biomarkers in informing decisions to stop antibiotic therapy remains unclear, especially in critically ill adults. Even fewer studies have been conducted in children. The economic impact of biomarker interventions is unknown. The goal of this project is to reduce unnecessary antibiotic use in the intensive care unit (ICU) setting. Phase I of the study will identify the biomarker(s) that best identify critically ill patients who have a very low likelihood of bacterial infection. In Phase II, the impact of a biomarker-based algorithm on reducing antibiotic use will be tested. Finally, we will expand the scope of the Delaware Valley Case Control Network (DVCCN) to address future CDC Prevention Epicenter initiatives. The specific study phases and aims are: Phase I: Test Characteristics of Candidate Biomarkers Aim 1: to assess the test characteristics of candidate biomarkers for identifying patients with very low likelihood of bacterial infection among critically ill adults Aim 2: to assess the test characteristics of candidate biomarkers for identifying patients with very low likelihood of bacterial infection among critically ill children The hypotheses for Aims 1 and 2 are that a biomarker or combination of biomarkers can be identified that demonstrates a high negative predictive value for bacterial infection Phase II: Impact of a Biomarker-Based Algorithm on Antibiotic Use Aim 3: to evaluate the impact of a biomarker-based algorithm on reducing antibiotic use in critically ill adults Aim 4: to evaluate the impact of a biomarker-based algorithm on reducing antibiotic use in critically ill children The hypotheses for Aims 3 and 4 are that use of the biomarker-based algorithm will be associated with significant reductions in antibiotic use Secondary Aim 1: to determine incremental costs (savings) of the biomarker algorithm in adults Secondary Aim 2: to determine incremental costs (savings) of the biomarker algorithm in children Aim 5: to expand the scope of the DVCCN for future CDC Prevention Epicenter initiatives This work will provide crucial insights into the potential impact of biomarker-based algorithms on reducing unnecessary antibiotic use in critically ill patients. The well-established DVCCN collaborative will provide an exceptional network of clinical sites within which to conduct future CDC Prevention Epicenter initiatives